Top Data & Analytics Jobs

The Analytics Manager will lead marketing measurement strategy, manage a team of analysts, and optimize marketing effectiveness through data analysis and collaboration.

Drive product decisions for Brazil by owning team KPIs, performing analyses, building data assets, sizing impacts (A/B testing), and partnering with PMs, marketers and engineers to prioritise and measure product improvements and launches.

Lead product-focused risk analytics: design and scale risk data infrastructure, build control frameworks and metrics, partner with product, engineering, risk and compliance to reduce financial crime and ensure regulatory controls are effective.

Lead analytics for the Financial Crime Platform, partner with product and engineering to build metrics, pipelines, visualisations, and features for fraud/AML risk models, drive discovery and data-driven decisions balancing risk and customer experience.

Lead a team of product analysts to improve customer acquisition and engagement for Scalable Growth. Partner with product, engineering, and design to set goals, define KPIs, run experiments, and own data strategy and tooling. Drive roadmap for analytics infrastructure, communicate progress, and hire, coach, and develop analysts to maximise impact and speed decision-making.

Lead credit analytics for Wise's Spend Squad: validate and stress-test credit risk models, build forward-looking loss and delinquency forecasts, define credit data strategy and tooling, partner with data science and regional teams for launches, and hire and develop a team of analysts.

Partner with financial crime product teams to drive analytics for screening controls. Build and maintain data pipelines, create reports and visualisations, define and track key metrics, run discovery analyses to improve controls and customer experience, and collaborate with stakeholders to translate insights into product changes.

Drive analytics for Payment Operations to improve payment quality and efficiency. Build attribution models for quality lapses, incorporate AI into review processes, expose and visualise payment data, create reports and pipelines, track KPIs, and collaborate with senior stakeholders to turn insights into operational improvements.

Lead analytics for customer operations: build capacity planning and forecasting models, own data pipelines, develop predictive and causal inference analyses, track KPIs, standardise processes, and partner with operations, WFM, quality, and training to drive data-driven improvements.

Lead analysis of operational data to support decision-making. Build dashboards and reports, partner with operations stakeholders to identify process improvements, monitor KPIs, and inform strategic initiatives.